Title :
Coastal fog detection using visual sensing
Author :
Dian Zhang;Timothy Sullivan;Noel E. O´Connor;Randy Gillespie;Fiona Regan
Author_Institution :
MESTECH, Marine and Environmental Sensing Technology Hub, Dublin City University, Glasnevin, D9, Ireland
fDate :
5/1/2015 12:00:00 AM
Abstract :
Use of visual sensing techniques to detect low visibility conditions may have a number of advantages when combined with other methods, such as satellite based remote sensing, as data can be collected and processed in real or near real time. Camera-enabled visual sensing can provide direct confirmation of modelling and forecasting results. Indeed, fog detection, modelling and prediction are a priority for maritime communities and coastal cities due to economic impacts of fog on aviation, marine, and land transportation. Canadian and Irish coasts are particularly vulnerable to dense fog under certain environmental conditions, and offshore installations related to oil and gas production on the Grand Banks (off the Canadian East Coast) for example can be adversely affected by weather and sea state conditions. In particular, fog can disrupt the transfer of equipment and people to/from the production platforms by helicopter. Such disruptions create delays and the delays cost money. According to offshore oil and gas industry representatives at a recent workshop on metocean monitoring and forecasting for the Newfoundland and Labrador (NL) offshore, there is a real need for improved forecasting of visibility (fog) out to 3 days. The ability to accurately forecast future fog conditions would improve industry´s ability to adjust its schedule of operations accordingly. In addition, it was recognised by workshop participants that the physics of the Grand Banks fog formation is not well understood, and that more and better data are needed. In Europe, an EU COST action fog project, with objectives of reducing economic loss and fatalities, has also been created to develop advanced methods for very short-range forecasts of fog and low clouds. Key research objectives of the project included methods for determining the optimal combination of satellite and ground-based observations and measurement techniques of fog. These data were then used to develop estimates of fog risk at high spatial and temporal resolutions, however the focus was on remote satellite observations rather than local visual sensing systems [1].
Keywords :
"Image color analysis","Histograms","Sensors","Image edge detection","Visualization","Cameras","Joints"
Conference_Titel :
OCEANS 2015 - Genova
DOI :
10.1109/OCEANS-Genova.2015.7271683